Management and workflow collaboration software systems are used by organizations to maintain the efficiency of workforces. Among other things, these systems, herein referred to as enterprise systems, allow employees to communicate, obtain information, requisition products and services, generate documents, and perform online training. Management systems may also connect portions of an organization that are separated geographically. As a result, management systems are often spread across multiple servers coupled to the network. The distributed nature of management systems along with the requirement that they perform numerous operations simultaneously makes them very large and complex.
Adding to the complexity of management systems is the fact that many of these systems have evolved over time. This evolution has largely been driven by customer needs and has resulted in rather basic management systems evolving into the large, complex ones predominant today. In addition, users must be able to write their own applications to extract maximum utility from management systems. The combination of old/new software-executable instructions and customer developed software instructions may produce operating environments that are difficult to troubleshoot. For example, an enterprise system may be executing hundreds or thousands of software agents as a matter of normal operation. A software agent as used herein refers to any self-contained potentially adaptive software application and as such is an executable sequence of instructions. Software agents can be short lived, i.e. having lifetimes of less than a second, or can be long-lived having lifetimes measured in hours or days. Furthermore, software agents may need to operate according to a schedule. If a particular software agent is not operating at the appropriate time, it may be due to either a problem with the scheduled agent, a problem with an agent currently running, or a problem with software processes that schedule agents. Identifying the exact cause of late agents using the prior art is thus problematic. Software agents may also consume system resources while operating. Examples of resources consumed by agents are, but not limited to, system memory, CPU bandwidth, disk input/output operations, database opens, document creation, and network traffic.
Prior art systems and methods for monitoring agent activity may not easily identify problematic agents because there is no apriori mechanism for identifying when agents may become problematic. Furthermore, prior art tools may not isolate problematic agents because they rely on sampling agents at discrete time intervals.
There exists a need for systems and methods for identifying agents that may become problematic before they actually cause a problem. Furthermore, there exists a need for monitoring system resources consumed by software agents. In addition, there is a need for identifying and rank ordering agents causing problems so that system resources can be adaptively managed.